Multiscale mathematical models for
simulation and scale-up of green
processes in the perspective of industrial
sustainability
Ph.D. in Mathematical Engineering & Simulation
Matteo Neviani
Supervisor: Professor O. Paladino
Professor R. Cianci
Department of Mechanical, Energy, Management and Transportation
Engineering (DIME)
University of Genoa, Polytechnic School
This dissertation is submitted for the degree of
Doctor of Philosophy
A
BSTRACT
The present work presents research studies aimed at developing tools useful to design engineering solutions moving in the direction of industrial sustainability. The investigations hereinafter discussed regard an extraction process of active compounds – polyphenols – from agro-food industry wastes (olive and grape pomaces) and a biorefinery exploiting waste frying oil, solid organic wastes and algal biomass to produce biofuels. In particular, for the former topic, a procedure aimed at the evaluation of the technological feasibility at pilot scale of said process is discussed. The proposed approach takes into consideration the extended kinetic route coupled with mathematical simulation. Detailed physically-based dynamic mathematical models, taking into account mass and energy balance equations, are adopted to describe both the lab-scale and the pilot-scale reactors. Chemical physical parameters appearing in the models are estimated from the experimental data at lab-scale or are partially taken from literature. Different heating systems are designed for the pilot scale reactor and their performance is tested by simulation. Characteristic times are evaluated also during start-ups and different control loops are analyzed in order to set-up the best process and operating variables. Average yields in polyphenols are finally evaluated for both the batch and the continuous operated pilot reactor, by considering feed variability and fluctuations of process parameters.
For what concerns the biorefinery, special attention was devoted to the modeling of the airlift reactor, its most delicate and complex component. In fact, to optimize this interesting microalgae cultivation system, a precise description of the moving interfaces formed by the liquid and gas phase is critical. In this study, coupled front capturing methods (standard and conservative level set methods) and finite difference method are used to simulate gas bubbles dynamics in a pilot-scale external loop air-lift photobioreactor in which microalgae are used to capture CO2from flue gas and to treat wastewater. Numerical simulations are carried out
on rectangular domains representing different sections of the vertical axis of the riser. The data employed was either acquired from previous experimental campaigns carried out in the
airlift reactor or found in the literature. The rise, shape dynamics and coalescence process of the bubbles of flue gas are studied.
Moreover, for each analyzed applications, a procedure based on Buckingham π-theorem to perform a rigorous scale-up is proposed. In this way, scale-invariant dimensionless groups describing and summarizing the considered processes could be identified. For the research focused on the scale-up of photobioreactors used to cultivate Chlorella Vulgaris, an experimental campaign at three levels was designed and carried out to evaluate the characteristic dimensionless numbers individuated by the theoretical formulation. Since scale-up regards both geometrical dimensions and type of reactor, passing from lab-scale stirred tanks to pilot scale tubular and airlift, particular attention was devoted to define characteristic lengths inside the dimensionless numbers.
P
REFACE
This thesis deals with issues related to environmental and energy engineering pursuing a mathematical modeling perspective. This latter was obtained through the extensive use of physically-based models, a macroclass of models chosen due to the fact that they typically involve physically interpretable parameters, allowing deeper insights into system performance and better predictions with respect to phenomenological models. The studies carried out did not focus on a single topic, but rather tackled different problems. In particular, two can be distinguished: the first is related to the valorisation of agro-food waste, while the second concerns the design of a closed-loop integrated pilot plant, pressing markedly on its most complicated component, i.e. the photobioreactor.
The works published and/or submitted to international scientific journals and congresses that constitute the framework on which this thesis was drafted, are explicitly referenced in the pertinent chapters and summarized in the continuation of the present preface.
In summary, the structure of the thesis is organized in such a way as to lend itself to a dual mode of reading: by applications and methodologies, meaning, in a way, by rows and columns. The reader in fact can either proceed sequentially through each chapter, which concerns the methodology/topic (introduction, modeling and scale-up), or skim through different chapters and follow the discussion about the application (mainly photobioreactors and process for the valorisation of agro-food waste).
A brief overview of the different parts of the thesis is presented below.
• Introduction. The purpose of this first chapter is to provide a cohesive and compre-hensive framework in which the research carried out is to be inserted. The problems and their origins are then presented, subsequently speaking about the technologies and resources used to address them. To this end, inspiration was drawn from:
– Hodaifa G., Paladino O., Malvis A., Seyedsalehi M., Neviani M. (2019). Green Techniques for Wastewaters. In G. Z. Kyzas (Ed.), Advanced low-cost separation techniques in interface science. London, UK: Elsevier.
Two technological examples are discussed more in depth, while their modeling and simulation is left for subsequent chapters. The work on these latter processes and devices were reported in the following scientific papers:
– Neviani M., Aliakbarian B., Perego P., Paladino O. (2019). Extraction of polyphe-nols from olive pomace: mathematical modelling and technological feasibility in a high temperature and high pressure stirred reactor. Chem. Eng. Res. Des. 141, pp- 32-46.
– Paladino O., Neviani M., (2018). A closed loop biowaste to biofuel integrated process fed with waste frying oil, organic waste and algal biomass: feasibility at pilot scale. Renew. Energy. 124, pp. 61–74.
– Paladino O., Neviani M., Moranda A., (2016). Feasibility Study of a Pilot scale Integrated Biowaste to Biofuel System fed with Waste Frying Oil, Organic Waste and Algal Biomass. Proceedings of the 6th International Symposium on energy from Biomass and Waste, Venice, Italy.
• Dynamic modeling. Chapter 2 hinges on the development of mathematical models for the simulation of the extraction of active compounds (polyphenols) from olive and grape industry organic waste. Hence, dynamic models of discontinuous and continuous reactors are presented and discussed.
The results are presented mainly in the article:
– Neviani M., Aliakbarian B., Perego P., Paladino O. (2019). Extraction of polyphe-nols from olive pomace: mathematical modelling and technological feasibility in a high temperature and high pressure stirred reactor. Chem. Eng. Res. Des. 141, pp- 32-46.
Also, some aspects of the process there discussed and modeled are treated in:
– Neviani, M., Paladino, O., An approach based on the π-theorem for the scale-up of polyphenols extraction for wide-ranging waste in a stirred reactor. Intended for submission.
• Local modeling apt to phenomenology study and control. In Chapter 3 a key component of a closed-loop integrated process for waste valorization is investigated under a modeling perspective. The behavior of such device, an external loop airlift photobioreactor, is analyzed through numerical methods.
vii
– Bagnerini M., Neviani M, Paladino O., (2019). Simulation of the rising of gas bubbles in a pilot-scale external loop airlift photobioreactor. Proceedings of the SUPEHR’19 – SUstainable PolyEnergy generation and HaRvesting Conference, Savona, Italy.
– Neviani M., Bagnerini P., Paladino O., (2018). A level set approach for computa-tion of bubble dynamics in airlift reactors. ISCRE25, Florence, Italy.
whilst theories and concepts taken up and organized in
– Paladino O., Hodaifa G., Neviani M., Seyedsalehi M., Malvis A. (2019). Mod-elling in Environmental Interfaces. In G. Z. Kyzas (Ed.), Advanced low-cost separation techniques in interface science. London, UK: Elsevier.
are used.
• Theoretical scale-up. Chapter 4 briefly introduce the theoretical foundation on which the scientific scale-up is built, successively presenting their application to the polyphe-nols extraction process discussed in Chapter 1 and 2, and to the algaculture system comprised in the closed-loop biorefinery examined in Chapter 1.
To this end, extensive reference has been made to:
– Paladino O., Neviani M. Scale-up of photo-bioreactors for microalgae cultivation by π-theorem. Under review.
– Neviani, M., Paladino, O., An approach based on the π-theorem for the scale-up of polyphenols extraction for wide-ranging waste in a stirred reactor. Intended for submission.
• Conclusions. In this last chapter conclusions are drawn and horizons for new research activities are discussed.
Appendix A show experimental data relative to the lab-scale polyphenols extraction process.
In Appendix B, detailed information on the materials employed for the experimental campaigns related to the study of the scale-up of photobioreactors for the cultivation of microalgae are presented. This information is contained in the following papers:
• Paladino O., Neviani M. Scale-up of photo-bioreactors for microalgae cultivation by π -theorem. Under review.
• Paladino O., Neviani M. Set-up of operating conditions in airlift photo-bioreactors for microalgae cultivation in integrated energy production processes. Under review. • Paladino O., Fissore F., Neviani M. A low-cost monitoring system and operating
A
CKNOWLEDGEMENTS
First of all, I would like to thank all the people that contributed, helped and influenced my work throughout my Ph.D. research studies.
To this end, I would like to start from my supervisor Professor Ombretta Paladino for her guidance, availability, patient support and kind advise. She was the first one to made me really savour the taste of research and laboratory investigation, offering me intellectual freedom in my work. I deeply appreciated your sharing your scientific knowledge with me, it was a privilege to keep on learning from you.
I also would like to acknowledge my co-supervisor Professor Roberto Cianci for his teachings and Professor Patrizia Bagnerini for her constructive suggestions and insightful comments, quintessential for completing my projects.
Besides them, my appreciations go to the whole ex-DIPTEM department section and in particular to my fellow Ph.D. colleagues for the consulting and the moments of lightness and laughter.
I cannot forget to externalize my appreciation for all my friends, old and new ones; each one of you shared moments, thoughts and a bit of your spirit with me, enriching me.
A special mention goes to Valentina, for her affectionate support throughout both joyous and tough times. Words can be empty, so I just say thank you, from the bottom of my heart.
At last but not least, my family. Their love and patience greatly supported me, pushing me to polish every aspect of myself, providing me with the tools to build my wings and leaving me free to spread them and fly as I see fit.
Matteo Neviani XXXI cycle
T
ABLE OF CONTENTS
List of figures xv
List of tables xvii
1 Chapter 1: Introduction 1
1.1 Environmental challenges in the new millennium . . . 1
1.2 Reduce, reuse and recycle . . . 5
1.2.1 An example of waste valorisation: polyphenols extraction from agricultural waste . . . 9
1.3 Biofuels . . . 12
1.3.1 The first generation . . . 15
1.3.2 The second generation . . . 17
1.3.3 The third generation . . . 19
1.3.4 The fourth generation . . . 21
1.4 Microalgae: a multipurpose environmental tool . . . 21
1.4.1 Microalgae culture systems . . . 22
1.4.1.1 Open systems . . . 25
1.4.1.2 Photobioreactors . . . 26
1.4.2 Wastewater treatment . . . 28
1.4.3 CO2sequestration . . . 29
1.5 Biorefineries . . . 30
2 Chapter 2: Dynamic modeling 43 2.1 Mathematical modeling of polyphenols extraction process . . . 43
2.1.1 Material balance for the reactor . . . 45
2.1.2 Kinetics of polyphenols extraction . . . 46
2.2 Simulation of the polyphenols extraction process . . . 52
2.2.1 Data-analysis and estimation of the extraction parameters . . . 52
2.2.1.1 Effects of solvents on polyphenols extraction rate . . . . 58
2.2.1.2 Estimation of extraction parameters for the process using grape pomace . . . 60
2.2.2 Development of the simulation model . . . 61
2.2.2.1 Parameter values used in simulation . . . 62
2.2.3 Scale-up results via simulation model . . . 64
3 Chapter 3: Local modeling apt to phenomenology study and control 71 3.1 Mathematical modeling of the ALR riser . . . 71
3.1.1 Navier-Stokes equations . . . 73
3.1.2 The level set method . . . 76
3.2 Development of the computational model of the ALR riser . . . 81
3.3 Grace’s diagram and the shapes of bubbles . . . 85
3.4 Simulation results with LSM . . . 88
3.5 Beyond LSM: the conservative level set method . . . 90
4 Chapter 4: Theoretical scale-up 99 4.1 Theoretical background . . . 99
4.2 Method of scale-up . . . 101
4.3 Scale-up of a microalgae cultivation system . . . 102
4.3.1 Outlining of the relevance list for batch microalgae growth in STRs 103 4.3.2 Determination of the dimensionless numbers for batch microalgae growth in STRs . . . 105
4.3.3 Outlining of the relevance list for microalgae growth in ALRs . . . 107
4.3.4 Determination of the dimensionless numbers for microalgae growth in ALRs . . . 108
4.3.5 Methods for evaluating the π-numbers . . . 111
4.3.5.1 Fluid dynamics in STRs and hydro-bubble dynamics in ALRs . . . 112
4.3.5.2 Mass transport . . . 114
4.3.5.3 Global kinetics of algae growth . . . 115
4.3.6 Computation of the π-numbers. Lab-scale STRs . . . 116
4.3.6.1 Fluid dynamics . . . 116
4.3.6.2 Mass transport . . . 117
Table of contents xiii
4.3.7 Computation of the π-numbers. Pilot-scale ALRs . . . 125
4.3.7.1 Fluid dynamics . . . 125
4.3.7.2 Mass transport . . . 126
4.3.7.3 Global kinetics of algae growth . . . 127
4.4 Scale-up of the polyphenols extraction process carried out in a DSTR . . . 127
4.4.1 Outlining of the relevance list for the polyphenols extraction process 128 4.4.2 Determination of the dimensionless numbers for the polyphenols extraction process . . . 129
4.4.3 Data-analysis and estimation of the relevance list parameters . . . . 131
4.4.3.1 Geometric data and fluid dynamics . . . 131
4.4.3.2 Mass transfer . . . 133
4.4.3.3 Extraction kinetics . . . 134
4.4.3.4 Heat transfer . . . 135
5 Chapter 5: Conclusions 141 Appendix A Polyphenols extraction process data 145 Appendix B Microalgae cultivation in PBRs. Experimental materials 149 B.1 Microalgae culture . . . 149
B.2 PBRs . . . 150
B.2.1 Discontinuous cultivation at lab-scale . . . 150
B.2.2 Semi continuous cultivation at lab-scale . . . 150
B.2.3 Continuous cultivation at pilot-scale . . . 151
B.3 Monitoring and automation . . . 153
B.3.1 Discontinuous cultivation at lab-scale . . . 153
B.3.1.1 Monitoring output variables . . . 153
B.3.1.2 Monitoring internal variables . . . 153
B.3.1.3 Operating mode and automation . . . 154
B.3.2 Semi-continuous cultivation at lab-scale . . . 154
B.3.2.1 Monitoring output variables . . . 154
B.3.2.2 Monitoring internal variables . . . 154
B.3.2.3 Operating mode and automation . . . 154
B.3.3 Continuous cultivation at pilot-scale . . . 155
B.3.3.1 Monitoring output variables . . . 155
B.3.3.2 Monitoring internal variables . . . 155
L
IST OF FIGURES
1.1 Observed indicators of climate change . . . 3
1.2 Linear vs circular economy . . . 4
1.3 Illustration of the 3Rs principle . . . 7
1.4 Projection of the world population . . . 8
1.5 Past and projected global waste generation . . . 9
1.6 Biofuels consumption vs crops production . . . 16
1.7 Microalgae exploitation . . . 23
1.8 The closed-loop integrated process . . . 31
2.1 Pilot-scale STR . . . 44
2.2 Pseudo-1storder model fitting for olive pomace and methanol . . . 54
2.3 Pseudo-1storder model fitting for olive pomace and ethanol-H2O (50:50) . 55 2.4 Peleg model fitting for olive pomace and methanol . . . 56
2.5 Peleg model fitting for olive pomace and ethanol-H2O (50:50) . . . 57
2.6 Effects of solvents ratio on TP extraction. . . 58
2.7 Pseudo-1storder model fitting for olive pomace and ethanol-H2O (50:50) at 180◦C . . . 59
2.8 Peleg model fitting for olive pomace and ethanol-H2O (50:50) at 180◦C . . 60
2.9 Pseudo-1storder model fitting for grape pomace and methanol . . . 61
2.10 Temperature in the pilot-scale reactor . . . 65
2.11 PRS on qin . . . 66
2.12 Volume oscillations . . . 66
2.13 TP yield for pilot-scale CSTR . . . 67
2.14 TP yield noise . . . 67
2.15 Temperature trends in the CSTR . . . 68
3.1 Illustration of the LSM . . . 77
3.3 Conceptual scheme of the ALR simulator . . . 82
3.4 Staggered grid with boundary cells . . . 82
3.5 Grace’s diagram . . . 87
3.6 Bubbles in the ALR . . . 88
3.7 Simulation of a single bubble (LSM) . . . 89
3.8 LSM correction method . . . 90
3.9 Simulation of multiple bubbles (LSM) . . . 91
3.10 LS functions comparison . . . 92
3.11 Remapping of ψ . . . 94
3.12 Boundary condition used for the CSLM simulation . . . 95
3.13 Simulation of multiple bubbles (CLSM) . . . 95
4.1 Microalgae culture scale-up representation . . . 103
4.2 Lab-scale DSTR fitted growth curves . . . 119
4.3 Lab-scale semi-CSTR fitted growth curves . . . 122
4.4 Measured DOxtrend . . . 124
4.5 Phases of algae growth. . . 124
B.1 Lab-scale semi-CSTR . . . 151
B.2 Pilot-scale ALRs . . . 152
B.3 ALR scheme . . . 155
L
IST OF TABLES
1.1 Pros and cons of all the four generations of biofuels (Dutta et al., 2014). . . 14
1.2 Land use and shares of crops used for biofuel production (WBA, 2017). . . 15
1.3 Main systems for microalgae cultivation: pros and cons. Adapted from (Hodaifa et al., 2019). . . 24
2.1 Pseudo-first order extraction rate: estimated parameters at different tempera-tures. Case of olive pomace (O.P.), dry mass : solvent ratio = 1 : 10 (Neviani et al., 2019). . . 54
2.2 Peleg extraction rate: estimated parameters at different temperatures. Case of olive pomace (O.P.), dry mass : solvent ratio = 1 : 10 (Neviani et al., 2019). 56 2.3 Extraction parameters and mean error estimate for olive pomace and ethanol-H2O (50:50) relative to the experimental run at T = 180◦C (Neviani et al., 2019). . . 59
2.4 Pseudo-first order extraction rate: estimated parameters at different tempera-tures. Case of grape pomace (G.P.), dry mass:solvent ratio = 1:5. . . 60
3.1 Data gathered in the experimental campaigns, from (Paladino and Neviani, 2018). . . 85
3.2 Physico-chemical data found in literature and employed in the simulations. 86 4.1 Base quantities and dimensions used in the SI (BIPM et al, 2008). . . 104
4.2 Relevance list for batch microalgae growth in STRs. . . 106
4.3 Relevance list for batch microalgae growth in an ALR. . . 109
4.4 Experimental tests carried out at lab-scale in discontinuous mode. . . 118
4.5 Results of the estimation of the kinetic parameters carried out through NLLS fitting. . . 120
4.6 Results of the estimation of the kinetic parameters carried out through WN-LLS fitting. . . 120
4.7 Optimal operating ranges of the input variables at DSTR lab-scale. . . 121 4.8 Measured and optimal operating ranges of the internal variables at DSTR
lab-scale. . . 121 4.9 Calibration curves at different wavelengths. . . 123 4.10 Results of the estimation of the kinetic parameters with NLLS and WNNLS
fitting for semi-continuous operation. . . 123 4.11 Main variables experimentally determined for the ALR operated in bubble
flow. τr,down is the downcomer residence time, while ¯dbis the mean bubble
diameter. . . 125 4.12 Main variables experimentally determined for the ALR operated in churn flow.125 4.13 Main hydrodynamic variables determined for the ALR by resorting to
empir-ical correlations. . . 126 4.14 Relevance list for the polyphenols extraction process carried out in a
semi-ideal isothermal DSTR. . . 129 4.15 π-space for the extraction process carried out at T = 180◦C with methanol
and olive pomace. . . 137 4.16 π-space for the extraction process carried out at T = 150◦C with methanol
and grape pomace. . . 137 A.1 TP yield extracted from olive pomace (Taggiasca cultivar) varying different
operative parameters of the lab-scale HPHT stirred reactor. . . 146 A.2 TP yield extracted from grape pomace (Croatina cultivar) varying different
operative parameters of the lab-scale HPHT stirred reactor. . . 147 B.1 Geometric data of the EL-ALRs. . . 153
1
C
HAPTER
1: I
NTRODUCTION
1.1
Environmental challenges in the new millennium
Already at the dawn of the new millennium, the sociocultural landscape presented new awareness and attention to environmental issues. The connotation of “green” associated with various areas, from the economic one to energy production, had assumed a popular character, symptom of a greater impact and a broader dissemination of these topics on public opinion. These are real issues that have to be tackled, not fictitious nor exaggerated.
Although the seeds of modern globalization began to sprout as a result of the Industrial Revolution and in conjunction with nineteenth-century imperialism, often its initial phase is placed in the last decades of the 1900s.
The aftermath of World War II, primarily under American guidance with its recipe of Rechtsstaat (rule of law), capitalism, and orientation to the stipulation of treaties and community policies, represented the period of the definitive change of pace on this front, which roughly starts from the Bretton Woods conference in 1944.
Globalization means also, above all, interconnection of markets, investments, people, ideas. It means the development of similar economic, industrial and technological models, at least for what concerns the most advanced countries.
The post-war years had brought a state of economic expansion to many countries. The generalized economic boom was linked to the new trend of lowering barriers and to free trade, actions deemed possible thanks to international agreements such as the General Agreement on Tariffs and Trade (GATT) of 1947, as well as the establishment of governance institutions such as the World Bank and the International Monetary Fund (IMF).
Scientific and technological innovations also played a central role, on par with the develop-ment and growth of the international connective tissue of transport and telecommunications.
Productive growth did not cease, continuing until the 1970s in the wake of the process started before the outbreak of the war. Industrial automation began to be available to a more widespread audience; the lower cost of natural gas and oil (at least until the crisis of 1973) meant that these raw materials supplanted coal in many countries.
A key aspect of this phase of globalized development was the lack of attention to the impacts it had on the environment.
The first studies and timid interventions with a view to environmental management are datable at the beginning of the twentieth century. However, it is not until the 60s and 70s that the first environmental regulations were promulgated and the first specific entities were established. Among the latter stands the birth in 1970 of the American Environmental Protection Agency (EPA) under the Nixon presidency and that of the international agency called United Nations Environment Program (UNEP) in 1972. UNEP, assisted by the World Metereological Organization (WMO), formed under the aegis of the United Nations the Intergovernmental Panel on Climate Change (IPCC) in 1988, which is to date the most important group of studies in charge of a scientific and objective analysis on climate change and its social and economic repercussions.
Nowadays there is awareness of how environmental problems do not only concern anthropogenic climate change – which translates among other things (see Fig. 1.1) into global warming, alteration of the hydrological cycle (hence desertifications, areas with scarcity of water resources but also increase in frequency of extreme weather phenomena such as floods and tornado formation), global dimming, sea level rise and ocean acidification –, but are also linked to overpopulation (with consequences on biocapacity, land degradation, waste generation), to industrial production (in particular with regard to consumption energy, still mostly fueled by fossil fuels), and to pollution and depletion of environmental resources (fragmentation or destruction of habitats and ecosystems, overfishing, intensive livestock breeding and farming).
The term sustainable development has thus entered strongly in the dictionary of policy makers and stakeholders. According to the perspective originally proposed by the French economist René Passet (Passet, 1979), sustainable development rests on three pillars: envi-ronment, economy and society. Thus a mutual interdependence manifests itself, which is coupled with the interconnection of nations as a result of globalization. The result is the impossibility of dealing individually with the challenges of sustainable development.
In order for the earth system to resist shocks and alterations resulting from the advance-ment of human civilization, a paradigm shift is required. Rather than relying on the resilience of our planet, ideally we should recognize humankind as an integral part of the biosphere, in the perspective of a balanced and harmonious growth of our societies.
1.1 Environmental challenges in the new millennium 3
Fig. 1.1 Multiple observed indicators of a changing global climate system. (a) Observed globally averaged combined land and ocean surface temperature anomalies (relative to the mean of 1986 to 2005 period, as annual and decadal averages) with an estimate of decadal mean uncertainty included for one data set (grey shading). (b) Map of the observed surface temperature change, from 1901 to 2012, derived from temperature trends determined by linear regression from one data set (orange line in Panel a). Trends have been calculated where data availability permitted a robust estimate (i.e., only for grid boxes with greater than 70% complete records and more than 20% data availability in the first and last 10% of the time period), other areas are white. Grid boxes where the trend is significant, at the 10% level, are indicated by a + sign. (c) Arctic (July to September average) and Antarctic(February) sea ice extent. (d) Global mean sea level relative to the 1986–2005 mean of the longest running data set, and with all data sets aligned to have the same value in 1993, the first year of satellite altimetry data. All time series (coloured lines indicating different data sets) show annual values, and where assessed, uncertainties are indicated by colored shading. (e) Map of observed precipitation change, from 1951 to 2010; trends in annual accumulation calculated using the same criteria as in Panel b (IPPCC, 2014).
Growth is the mantra repeated by every government. The role of science and technology also consists in trying to find solutions to continue to grow, allowing longer-lived lives in continuously improving conditions. This goal goes hand in hand with being compatible with the system that hosts us.
Fig. 1.2 Graphical representation of the concepts of linear and circular economy. Economic dynamics can be seen as a loop whose interactions with the planet are essential for the retrieval of natural resources and the absorption of waste and pollution. Endurance of the model is maintained until the load capacity of the planet is not exceeded. Whilst linear economy (left) neglects the environmental impacts deriving from the aforementioned interactions, taking on a segment characterization with a beginning (extraction) and an end (disposal), the circular one (right) also considers the consumption of resources and the waste flows towards the environment. Circular economy contemplates the material symbiosis between vastly different production processes and activities, emphasizing how the continuous exchanges with the various environmental matrices lead to further closed alternative cycles, proposing to optimize the use of virgin resources and reduce pollution as far as feasible (adapted from Sauvé et al., 2016).
On the other hand, the need to address issues together rather than individually also creates opportunities. Where this is probably most evident is in the waste sector. They are seen in a new light, as a potential resource. This new concept fits perfectly into that, now in the foreground as evidenced effectively by the recent policies of China (Geng et al., 2013), European Community (European Commission, 2015)) and other Asian states (Andersen, 2007), of a circular economy replacing the dominant open-ended linear model (see Fig. 1.2), also known as “take, make and dispose” development model (Ghisellini et al., 2016). In fact, circular economy is a locution that defines “an economic system that replaces the
‘end-1.2 Reduce, reuse and recycle 5
of-life’ concept with reducing, alternatively reusing, recycling and recovering materials in production/distribution and consumption processes by operating at the micro level (products, companies, consumers), meso level (eco-industrial parks) and macro level (city, region, nation and beyond) with the aim to accomplish sustainable development, thus simultaneously creating environmental quality, economic prosperity and social equity, to the benefit of current and future generations” (Kirchherr et al., 2017).
As evidence of the mentioned emergence of new opportunities following a more holistic approach on environmental challenges, one can think of the topic of biofuels. With the documented recognition of anthropogenic climate change, the search for alternative and greener energy supply sources has become more intense. Among the alternatives, biofuels are back in vogue. In a first phase (first generation), they were synthesized from food crops such as corn, soybean, palm and sugar cane, giving rise to an ethical debate. In order to overcome this major limitation, i.e. the creation of a potential competition for agricultural products between the energy and food production sectors, it was decided to exploit the biomass of agricultural residues as raw material, reaching the so-called second generation biofuels.
Subjects related to recycling and biofuels will be explored more in depth in Sections 1.2 and 1.3 respectively.
Section 1.5 deals with the issue of biofuel production through biorefineries and, more generally, the importance of creating closed-loop systems that follow the precepts of the circular economy, exploiting as much as possible any flow that interests them. In this regard the discussion on conversion processes operating thanks to biomass aimed at the production not only of fuels but also of energy, heat and added-value chemicals will be introduced. The technical study of one of the crucial and also delicate components of a particular closed-loop pilot plant of this kind will then be presented in detail in Chapter 3 whilst details on aspects relative to this plant can be found in Appendix B.
1.2
Reduce, reuse and recycle
Although a univocal definition of circular economy is still absent (the one previously provided is an attempt to standardize by drawing on various different definitions), it is widely believed that it interweaves different concepts including industrial ecology, the life cycle approach and the 3R principle.
Industrial ecology draws a parallel between industrial systems and ecosystems, empha-sizing the flows of matter and energy and how in networks of biological systems they tend to form feedback loops, recycling nutrients and energy in an integrated way (Hu et al., 2011).
The development of innovative systems that incorporate the vision of the circular economy also depends on the availability of tools apt to evaluate their potential and performance: in this sense, the currently most accepted methodology is the Life Cycle Assessment (LCA),with which the energy and environmental loads associated with a product are quantified, consider-ing all the stages of his life (Lijò et al., 2018).
Finally, the last mentioned ingredient is the so-called principle of the 3Rs, which stands for Reduce, Reuse and Recycle. Originally introduced as an answer to the management of Municipal Solid Waste (MSW), it is also taking hold in other areas, such as energy and industrial productions.
Imagining what this principle implies is easy: reduction implies putting the emphasis on the parsimony with which resources are exploited, as well as their careful choice, in order to minimize the waste products generated. Reusing means finding applications for which wastes or parts of them can be used, as such, again. Finally, recycling aims to enhance waste to create added value, by seeing them as raw material. Following the procedure just described, the quantity of material to be transferred to final disposals is minimized (see Fig. 1.3).
The continuous increase of world population that according to the last projections (see Fig. 1.4), although slightly lower than previous estimates, should reach 8.6 billions in 2030 (United Nations, Department of Economic and Social Affairs, Population Division, 2017), has a clear correlation with production of waste (see Fig. 1.5).
Given the amount of material, the sense of the institution of a waste hierarchy, from which follows the ordering of the 3Rs transpires even more markedly: to implement preventive maneuvers (up-stream solutions) rather than end-of-pipe type (down-stream) ones affects both management costs (industrial symbiosis adding value to wastes and source reduction versus waste collection, disposal and remediations costs) and the environment (Mohanty, 2011). Nonetheless, relying too much on final recovery practices, such as waste-to-energy, may not be sufficient or advisable: incinerators release a wide variety of pollutants depending on the composition of the treated matrix, with possible repercussions on health and causing environment degradation (Sharma et al. al., 2013). Recycling large quantities of materials requires adequate facilities for capacity and technology, assisted by effective sorting systems. Prolonging the useful life of products, attacking planned obsolescence, digitizing and stream-lining where possible, paying attention to new models such as the sharing economy while promoting the use of renewable energy sources are all actions referable to higher levels in the hierarchical pyramid of sustainable waste management.
Among the pioneers in the adoption of initiatives and policies centered on the 3Rs, following the agreement reached at the G8 Sea Island Summit in June 2004, is Japan (see in this regard the Basic Act for Establishing at the Sound Material-Cycle Society of 2000
1.2 Reduce, reuse and recycle 7
Fig. 1.3 The implementation of the 3Rs principle calls for three steps: the first is reduction, acting on both production (i.e. design, manufacturing, distribution, etc.) and consumption/use, then comes reuse, whose goal is to employ again discarded materials (or energy), and finally recycle. Recycle has an ambivalent meaning. It can refer both to the recovery of energy, where the waste to energy must be seen as the last resort, and to materials, which can not be re-used directly as raw materials.
implemented in 2003 with the Fundamental Plan (OECD, 2010), the 3R Initiative launched at Tokyo Conference in 2005 or the Kobe 3R Action Plan (Grosse, 2010)) but soon many other countries have begun to conform (Visvanathan and Kumar, 2007), at least for certain sectors (e.g. RRR Directive 2005/64/EC of the European Union on the recovery, reuse and recycling of motor vehicles). Even companies and corporations are following virtuous propositions, as witnessed for example by the announcement at the 2018 Word Economic Forum (WEF)
Fig. 1.4 Probabilistic projections of the world total population, built upon the probabilistic projections of total fertility and life expectancy at birth, based on estimates of the 2017 Revision of the World Population Prospects. These probabilistic projections of total fertility and life expectancy at birth were carried out with a Bayesian Hierarchical Model. The figures display the probabilistic median, and the 80 and 95 per cent prediction intervals of the probabilistic population projections, as well as the (deterministic) high and low variant (+/- 0.5 child) of the 2017 Revision of the World Population Prospects (United Nations, Department of Economic and Social Affairs, Population Division, 2017b).
that several giants such as The Coca-Cola Company, Walmart, PepsiCo and L’Oréal are committed to have all their packaging reused, recycled or composted by 2025.
Efforts to adopt a philosophy oriented to a cradle-to-cradle analysis of the various products are being spent in various fields: electrical and electronic waste, the aforementioned optimization of the life cycle of the products of the automotive industry, plastic waste management and so on.
The discipline of waste management, pursuing a pragmatic line, has established different degrees of priority based on the risk associated with each type of waste, taking into account proximity to the population and characteristics of the waste. If special attention is devoted to Municipal Solid Waste (MSW), waste management systems should therefore take into greater account the derivatives of all the life-cycle of products, intervening also on mining
1.2 Reduce, reuse and recycle 9
Fig. 1.5 Chart of global waste production with forecasts to 2100 that are based on three different scenarios. In the first Shared Socioeconomic Pathway scenario (SPP1) the world population stands at 7 billions, is 90% urbanized, more environmentally responsible, and boasts achievements of development targets, with reduction in the use of fossil fuels. The SSP2 projection considers a more conspicuous population, standing at 9.5 billions, inhabiting for the 80% in cities and does not consider large deviations from today’s economic-industrial conditions. Finally, in SSP3, 70% of about 13.5 billions people live in an urban context of moderate wealth with pockets of extreme poverty and many rapidly growing demographic nations (adapted from (Hoornweg et al., 2013)).
and quarrying (extraction) wastes, byproducts of construction and demolition activities, agriculture and forestry wastes.
To this end, it is noted that, according to the Food and Agriculture Organization, 1.3 billion tons per year, roughly equivalent to one third of the food produced, turns into food waste. Being an organic material containing a wide range of compounds, this matrix is a useful resource for the production of value-added chemicals (Chen et al., 2017). In the following subsection, an idea that moves precisely in this sense is presented.
1.2.1
An example of waste valorisation: polyphenols extraction from
agricultural waste
When talking about sustainability and focusing on the social aspects, health evidently holds a primary importance. It is common knowledge that diet plays a crucial role in this aspect. For example, Mediterranean diet is widely appreciated throughout the world also because of
the low incidence of atherosclerotic diseases associated with it. Its high content of active ingredients, such as oleic acids and phenolic compounds, in particular those coming from olives and grapes, determines a significant antioxidant, anti-inflammatory, antimicrobial, cardioprotective and chemoprotective properties (Nassiri-Asl et al., 2016; Carluccio et al., 2003). In addition to the conspicuous ingestion of plant-based food, the moderate consumption of white and fish meat and the low intake of red meat, red wine and olive oil are in fact notable constituents this dietary pattern (Martínez-Huelamo et al., 2017).
The wine-making and oil mill industries are paramount standard bearers for the agro-industrial activity, and therefore for the economies, of the Mediterranean regions. To olive oil 30 million tons per year of waste by-products streams are due, the main exponent of which is olive pomace (Chandra and Sathiavelu, 2009), which has a heterogeneous solid nature. After milling, only 2% of the phenolic compounds in the olives are transferred to the oil. Hence, the olive pomace shows high concentrations of polyphenols (Di Nunzio et al., 2017).
Similar remarks can be made for the wine industry: as a result of practices such as pruning and exfoliation, vinification and distillation, the equivalent of almost 25% of the inputted grape is processed into grape pomace (Makris, 2018).
Recovery of phenolic compounds from this cheap and widely available biomass and their further application in food, cosmetic, and pharmaceuticals has been recognized as a valorization strategy for olive oil industries. Several processes have been examined for the extraction of polyphenols from olive pomace via conventional solid–liquid extraction or nonconventional techniques (Paini et al., 2016) and, among all, High-Pressure/High-Temperature Extraction (HPHTE) showed to be highly effective (Casazza et al., 2012).
The study of various operational parameters for the aforementioned type of extraction, already carried out for the olive pomace in a laboratory scale mixed reactor (Aliakbarian et al., 2011), has been extended to the case of extraction from grape pomace as well. Following these promising results and considering the industrial interest in the exploitation of pomaces, the feasibility study of up-scaling of the extraction technique using a mini-pilot reactor was conducted.
To do so, the extraction kinetic parameters were firstly estimated by the experimental extraction data, and a complete simulation model of the lab-scale reactor was tuned (heat transport and mixing parameters) in order to evaluate characteristic times at lab-scale.
A pilot scale mixed reactor was designed, and subsequently simulated with different possible heating systems and in different operating conditions, both in batch and in continuous. The dynamic behavior of the reactor was also studied by changing parameters values and simple control strategies were tested on the pilot-scale dynamic model. More details on this modeling and its results are given in Chapter 2.
1.2 Reduce, reuse and recycle 11
As matrices from which to obtain the phenolic compounds, Taggiasca cultivar olive pomace supplied by a producer located in Liguria and Croatina cultivar grape pomace, provided by a Piedmontese winery have been employed. The grape pomace, collected after vinification and dried for 24 hours at 40◦C, subjected to grinding for 20 seconds in order to avoid heat generation and degradation of the polyphenols, was stored in a sealed container at −20◦C. The olive pomace, deriving from three-phase oil extraction from a decanter, was instead stored at 20◦C before analysis.
At laboratory scale, the extraction process was carried out in a Pressure High-Temperature (HPHT) model 4560 (Parr Instruments Company, Moline, IL, USA) stirred discontinuous tank reactor. Its AISI 316 stainless steel cylindrical vessel, moveable and of tunable volume (0.1 L ÷ 0.6 L), is equipped with appropriate valves for the introduction and removal of gases inside the reaction chamber. As safety feature for pressure relief, a rupture disc is present. A pressure gauge and an internal thermocouple allows for temperature and pressure monitoring, while heating is achieved through a heating mantle. Temperature, along the entire duration of the extraction process, was maintained constant.
Every experimental test was carried out under nitrogen atmosphere so as to avoid the effect of an extractive atmosphere, meaning phenolic oxidation and gas phase extraction. Internal pressure was directly proportional to the required temperature to keep the solvent in liquid phase, so it was related to the chosen extraction solvent. Pressure of about 33 bar was measured at 180◦C by using methanol as a solvent, while a maximum pressure of 17 bar was measured at the same temperature using H2O:ethanol (50:50).
Another feature of the compact reactor is that the inner liquid solution, mixed by a magnetic stirrer, can be recovered thanks to a liquid outlet valve.
Instead, at pilot scale, we availed ourselves of a 16 L stirred AISI 316 stainless steel reactor which can be operated either as a Discontinuous Stirred Tank Reactor (DSTR) or Continuous Stirred Tank Reactor (CSTR). Said reactor is geared with resistor wires, wrapped around and welded to the reactor lateral walls, that generate heat via Joule’s effect. These wires are electrically insulated from external tubular sheaths in which they are inserted through the use of mineral insulation (magnesium oxide); this latter is also an excellent thermal conductor, aiding heat transmission to the outer tubular sheath. The system encompasses temperature self-regulation capability through a designated control system. While the resistor wires heating device is not suited for industrial scale reactors, it better approximates the heating system with which the lab-scale reactor is equipped, an important feature when considering testing scale-up results.
In order to gauge the Total Polyphenol (TP) concentration, a UV–Vis spectrophotometer (Model Lambda 25, Perkin Elmer, Wellesley, MA) at a wavelength of 725 nm and the
colorimetric Folin–Ciocalteau assay (Swain & Hillis, 1959) were deployed. The calibration of the total polyphenol concentration, expressed as microgram of equivalent caffeic acid per grams of dried pomace, was carried out (coefficient of determination R2= 0.999) by means of standard methanolic solutions of caffeic acid (10 ÷ 1000 µgCAEmL-1). A summary of the
experimental results is shown in Table A.1 and Table A.2 in Appendix A.
1.3
Biofuels
Another angle from which it makes sense to try to essay environmental challenges, especially for what concerns the development of reliable and sustainable energy sources, is the tangible implementation of biofuels in real economy.
The world energy demand is expected to continue to increase, with a growth rate estimated (Bosch et al., 2018) by the World Energy Council (WEC) and the International Energy Agency (IEA) of between 17 and 56% for the period 2015 ÷ 2050 (from 563 EJ to between 663 and 879 EJ). Although fossil hydrocarbons and its derivatives are still predominant (and will probably be in the near future), the outlook sees a significant boost towards renewables, as shown by the IRENA data that estimate the transition of total installed power from renewable sources from 1058 GW in 2008 to 2179 GW in 2017 (IRENA, 2018).
In order to limit carbon dioxide (CO2) emissions, the main contributor to the quantity of
GreenHouse Gases (GHGs) released, we need to focus not only on power generation but also on the transport sector. In fact, since 1990, the emissions linked to it have increased by more than 50%, earning the primacy for fastest growing CO2source and weighing for 25% of the
total emissions of carbon dioxide from combustion of fuels (Varone and Ferrari, 2015). The major investments in the transition to renewables are focusing mainly on wind and solar. These technologies are intrinsically linked to a scarcely predictable and variable energy output due to the stochastic and intermittent nature of such energy sources. Therefore, they require the development of efficient electrical storage systems and a further increasing interpenetration of the various production systems in order to better balance the load on the supply grid. With regard to this point, digitalization is emerging as an important actor because the convergence in the use of artificial intelligence, cloud and Blockchain for energy systems seems to offer good promises in the key of smart grids, potentially expanding renewable energy from a niche resource to one with a wider pool of participation (prosumers) in the supply mix (WEC, 2018). From this it would seem to follow an electrification also of mobility and certainly many automotive brands are moving in this direction. Nevertheless, biofuels are seen by many as the key alternative for curbing the carbon footprint of the transport sector, at least in a medium-short horizon. Moreover, the main upside of biofuels is the
1.3 Biofuels 13
possibility of exploiting the preexisting distribution and transport infrastructures, all without requiring alterations to the locomotion system, which remains the internal combustion engine nor prolongations of the refueling time (Brutschin and Fleig, 2018).
Taking as a reference the results of the mobility model presented by the IEA for its 2◦C scenario (in which a path for the energy system and a trajectory for the CO2emissions
that would ensure at least a 50% probability of limiting the average global temperature increase of at 2◦C by 2100 is layed out), the biofuels’ share of overall fuel consumption for transportation will amount to 30.7%, followed by 27% of electric vehicles. A similar future would require, considering the projections of the demand, a 10-fold increase in the production of biofuels (Oh et al., 2018).
Europe is at the forefront on this matter and, with the January 2018 amendments to its directive known as the post-2020 EU Renewable Energy Directive (RED II), imposes constraints with a dual purpose: phase out first generation biofuels that feast on edible biomass while promoting, with a binding mandate, the most advanced ones (second and third generation, possibly fourth). The limits for 2030 are thus set at 7% for first generation biofuels and 10% for those of subsequent generations (Doumax-Tagliavini and Sarasa, 2018). In this context, it should also be kept in mind that currently 90% of biofuels belong to the first generation.
Currently, the two most widely used biofuels are biodiesel and bioethanol: to offer some supporting data, of 126 billion liters of liquid biofuels produced in 2014, 78 were bioethanol and 32 biodiesel, with the United States and Brazil as the largest contributors (WBA, 2017). The former is mainly used as an additive in gasoline mixtures in different percentages: E15 (15% ethanol, remaining gasoline) and E85 (85% ethanol, 15% petrol) in primis. The conversion technology employed to synthesize it is function of the feedstock. However, bioethanol, nowadays produced primarily as a first-generation biofuel from corn (in China, USA and European Union) and sugarcane (in tropical countries), is obtained in most cases through a production process articulated in three fundamental phases: the first one consists in obtaining the solution containing fermentable sugars, followed by the conversion sugars into ethanol (CH3CH2OH) by fermentation and finally by the separation and purification of
CH3CH2OH, generally by distillation, rectification and dehydration (Lin and Tanaka, 2006).
Further details on bioethanol production can be found for example in (Vohra et al., 2014). Biodiesel, on the other hand, is a fuel derived not necessarily from vegetal matrices: aside for vegetable oils, it can also be synthesized from animal fats. The key component of both these resources, which can not be used directly as fuels primarily due to damage that their high viscosity could cause to the engine, are triglycerides, or fatty acid esters. It follows that the most frequently followed route (Chakraborty et al., 2016) is that of Trans-Esterification
Table 1.1 Pros and cons of all the four generations of biofuels (Dutta et al., 2014).
Generation Advantages Disadvantages
1st
GHG savings; Low yield;
Simple and low cost Cause food crisis as a large conversion technology. portion arable land required for
growing crops.
2nd
GHG savings; Costly pretreatment of
Utilize food wastes as feedstock; lignocellulosic feedstock highly No food crop competition; advanced technology need to be Use of non-arable land for developed for cost effective growing few energy crop. conversion of biomass to fuel.
3rd
Easy to cultivate algae; More energy consumption for Higher growth rate; cultivation of algae (for mixing, Versatility: can use filtration, centrifugation, etc.); wastewater, seawater; Low lipid content or biomass No food crop competition. contamination problem in open
pond system;
High cost of photo-bioreactor.
4th
High production rate; Initial investment is high; High yield with high lipid Research is at its primary stage. containing algae;
More CO2capture ability.
(TE), assisted or not by heterogeneous, homogeneous or enzymatic catalysis, with which such drawbacks are obviated. Generally, this procedure give rise to a mixture of Fatty Acid Methyl Ester (FAME), whose quality must comply with appropriate standards (mainly the American standard, ASTM D-6751, or the European one, EN 14214). A less widespread alternative involves the use of pyrolysis (Sharma and Singh, 2009). For a review of the technologies for the production of biodiesel the work of (Abbaszaadeh et al., 2012) is suggested.
If it is true that first generation biofuels are predominant, more advanced alternatives are emerging. Numerous studies are focused on the exploitation of waste cooking oils, non-edible lignocellulosic biomass, microalgae, non-edible seed oils, and even manure (Gomaa and Abed, 2017). Nonetheless, research has yet to advance as even third and fourth generations present pros and cons. The main ones are listed in Table 1.1, while a more detailed discussion is reported in the following subsections.
1.3 Biofuels 15
1.3.1
The first generation
As mentioned earlier, biofuels that are produced from food crops, for animals or humans, are classified as belonging to the first-generation.
The renewable adjective is given to biofuels because the feedstocks necessary for their manufacture can be replenished way quicker than those of fossil fuels. Moreover, their use is said to reduce the emissions of GHGs not because their combustion does not release them but rather for an improvement by subtraction: feedstocks from which they are synthesized are an integral and active part of the carbon cycle. Plants, through photosynthesis, remove and sequester carbon dioxide from the atmosphere, which is released again during their combustion. On the contrary, using fossil fuels means introducing CO2 from outside the
carbon cycle, since it comes from reserves buried in Earth’s crust for million of years. On closer inspection, however, the carbon footprint balance may not be so positive if a cradle-to-cradle approach is adopted. One of the main criticisms of first generation biofuels is that, when carbon dioxide output flows relative to the farming, transport and fertilizer production processes (which often rely on fossil fuels) are taken into consideration, the concept of carbon neutrality can become even significantly distant (Fargione et al., 2008).
The main downside of first generation biofuel implementation remains the one related to land use. Ceding plots of land to plants for fuel production raises obvious ethical questions. The repercussions in this sense are not only direct: fluctuations in demand, and therefore in prices, can push farmers towards the removal of portions of grasslands and forests to widen their agricultural fields and increase production, undermining biodiversity and the lunging capacity provided by plants. Some data, referred to 2014, is reported in Table 1.2 and Figure 1.6.
Table 1.2 Land use and shares of crops used for biofuel production (WBA, 2017). Biofuel Crop Production (Mt) Biofuels (Mt) % of biofuels use
Bioethanol wheat 720 2.62 0.4 maize 1014 53.20 5.2 other grains 299 4.16 1.4 sugarbeet 257 1.11 0.4 sugarcane 1812 25.3 1.4
Biodiesel palm oil 61 23.2 37.9
Fig. 1.6 Consumption of biofuels and shares of biofuels in major crops production (WBA, 2017).
First-generation bioethanol currently holds the record for production, with more than 85% of it deriving from wheat, maize and sugarcane (Table 1.2). Studies that have investigated the effectiveness of this latter feedstock for various maturity levels has shown that the best yields occur in the interval 300 ÷ 325 days after planting (Rolz and de León, 2011).
Biodiesel, which regardless of generation, is obtained primarily by trans-esterification through the use of methanol (CH3OH) or, less commonly due to its higher price, ethanol
(C2H5OH) to form Fatty Acid Methyl Esters (FAMEs) and Fatty Acid Ethyl Esters (FAEEs)
respectively, has vegetable oils as its widest source. Considerable conversion yields have been reported, for example of 77% for its generation from cottonseed oil with 0.5% sodium hydroxide (NaOH) and 20% methanol (Nabi et al., 2009).
1.3 Biofuels 17
Another alternative, although much less adopted, is biogas, which can be obtained starting from anaerobic digestion of manure and other organic biomass (Naik et al., 2010).
1.3.2
The second generation
It is recognized that second generation biofuels offer numerous advantages not only with respect to fossil fuels but also to first generation biofuels. These include a better energy balance, a marked reduction in greenhouse gas emissions, overcoming the problem of competitiveness with food of the seasonality of production, with obvious positive influences on plant productivity (IEA Bioenergy, 2008).
Second-generation biofuels have evolved independently of previous generation biofuels. They instead represent products from new industrial dynamics, which have become part of the so-called bioeconomy, in which biomass-based products have been increasingly available as food, feed, energy and biomaterials. Second-generation biofuels can be a lower carbon option than first-generation biofuels in terms of their effects. According to the International Energy Agency (IEA), second-generation biofuels are produced from cellulose, hemicellulose or lignin. Such biofuels can be blended with petroleum-based fuels or used in adapted vehicles (Eisentraut, 2010). Cellulosic ethanol and Fischer-Tropsch fuels are an example of second generation biofuels. Second-generation biofuels yield greater energy output than fossil fuels, include a much larger array of feedstock options (Carriquiry et al, 2011), minimize competition on land and have much less environmental impacts.
Second generation biofuels are produced from non-edible ligno-cellulosic materials, entailing by-products such as forest residues (e.g. sawdust (Stoffel et al., 2017), bark (Frankó et al., 2015), hardwood chips (Perego et al., 1990)) and cereal straw (e.g. rice husk (Saha et al., 2005) and wheat straw (Hongzhang and Liying, 2007)), wastes, intended both as organic fraction of MSWs (food waste and paper sludge containing cellulose (Prasetyo et al., 2011) for example) and industrial wastes (e.g. spent grains from distilleries (Kricka et al., 2015)), and purpose grown energy crops (e.g. miscanthus (Lee and Kuan, 2015) and fast-growing poplar (Koukoulas, 2016)). The latter can be produced in marginal lands (Robak and Balcerek, 2018) but such a choice can affect yield, since it is obvious that a worse soil quality, in the absence of adequate supplies of water and nutrients, determines a yield declination over time. Regarding this aspect it is important to underline how, compared to first generation biofuels, lignocellulosic crops reach higher yields per unit area (J ha−1). The main constituents of lignocellulosic biomass are (Bajpai, 2016) cellulose (40 ÷ 55%) and hemicellulose (25 ÷ 40%), polysaccharides that embody an important pool of potential sugars. The hydrolysis of these two polymers compounds produces fermentable sugars, giving rise to one of the main methods for producing advanced biofuels. Following such a
path allows the exploitation of the whole plant to obtain mixtures of fermentable sugars to be used as raw material in the production of advanced biofuels, whereas for first generation biofuels only a small fraction (cereals and seeds) of the biomass available is used. Direct fermentation is not practically feasible as grasses, wood and uneatable parts of the plants are tougher to break down and therefore require pre-treatments, categorized into four main groups: chemical, physical, physic-chemical and biological (Kumar et al. 2009).
Together (Luque et al., 2016) with the combination of hydrolysis and fermentation (biochemical route), the other main way to obtain second-generation biofuels is to follow the thermochemical route, i.e. high temperature heating of the biomass either in the absence (pyrolysis/torrefaction) or presence (gasification) of O2, air and/or steam. Direct liquefaction
and supercritical fluid extraction complete the picture of the exponents of this class (Demirbas, 2001).
Hydrolysis, be it acidic or enzymatic, preceded by pretreatment and followed by fermen-tation is the most common process for the production of bioethanol, in turn distinguishable in Simultaneous Saccharification and Fermentation (SSF), Separated Hydrolysis and Fermen-tation (SHF) or Simultaneous Saccharification and Co-FermenFermen-tation (SSCF) (Mohd Azhar et al., 2017). The constituents of cell walls of the plants, i.e. cellulose and hemicellulose, are separated from lignin and simple sugars are obtained from their hydrolysis; the subsequent stages of fermentation, distillation and refining follow those of the conventional bioethanol production process.
Following the thermochemical path allows for shorter conversion times and usually involves the generation of liquid fuels, hence the name Biomass-to-Liquid (BtL) synthesis, passing through an intermediate step of biomass to synthesis gas transformation. Important features of BtL biofuels are the low emissions of NOxand CO2, the adaptable quality of
the products (cetane and octane number) and the complete elimination of emissions of particulate matter (Swain et al., 2011). Among the BtL processes, currently those that employ gasification or pyrolysis and the Fischer-Tropsch process are in the foreground (Ibarra-Gonzalez and Rong, 2018). The Fischer-Tropsch synthesis (FTS) consists of the production of single chain aliphatic hydrocarbons starting from a synthesis gas (syngas) derived from gasification, rich in carbon monoxide (CO) and hydrogen (H2), with a reduction of the
former by the H2in temperature conditions between 170 ÷ 220◦C and pressure of 1 ÷ 10
atmospheres. In this way, for example, FTS biodiesel is obtained. In addition to the aliphatic hydrocarbons, branched hydrocarbons, unsaturated hydrocarbons and primary alcohols, in lower quantities, are present in it as well (Bartocci and Cavalaglio, 2008). Biomethanol and bio-dimethyl ether (DME) are other biofuels obtainable from syngas. The former is produced by hydrogenating the carbon oxides present in the synthesis gas, derived from gasification
1.3 Biofuels 19
or pyrolysis, in fixed bed reactors with pelletized catalyst (Cu/Zn/Al). The reactions are exothermic and determine a net decrease in the molar volume (Bartocci and Cavalaglio, 2008). On the other hand, DME (CH3OCH3) can be obtained either by the dehydration of
methanol (and therefore also biomethanol) or by its direct generation starting from the syngas (Swain et al., 2011).
The lignocellulosic biomass can also be used for the purpose of biohydrogen synthesis. Again, different strategies can be adopted: single-step direct production is reported as the most cost effective and commercially viable. It is based on the action of thermophilic bacteria such as Clostridium thermocellum which produce hydrogen following the production of cellulolytic enzymes for effective hydrolysis (Cheng et al., 2011).
Other sources of primary importance in the discussion of second generation biofuels are vegetable oils, whether they come from inedible seeds, such as Jatropha curcas, or from animal and vegetable waste oils, Waste Cooking Oils (WCO) in particular (Bhatia et al., 2017). Typically, they assume the role of lipid sources for transesterification for the purpose of obtaining biodiesel and are available at low prices.
Finally, residues generated in the food industry and during the production of first gen-eration biofuels can be employed as substrates for the synthesis of second gengen-eration ones. The case of glycerol, the main by-product of the biodiesel and bioethanol industries, is interesting in this sense (Yazdani and Gonzalez, 2007). Glycerol (C3H8O3) can be fermented
using microorganisms and used for bioethanol production. The fermentation is, for example, carried out by converting pyruvate or phosphoenolpyruvate (PEP), leading to a higher yield of bioethanol and content of reducing equivalents compared to the fermentation of xylose and glucose from the biomass (Robak and Balcerek, 2018). The advantages of a similar use of glycerol are the simplification of the process and the consequent cost reduction.
1.3.3
The third generation
Biofuels synthesized from lipids deriving from oleaginous microorganisms, such as bacteria, yeasts and fungi and algae form the third generation (Leong et al., 2018). Oftentimes, however, the latter is juxtaposed exclusively to the fuels produced by algal biomass, referring in particular to microalgae. In fact, the interest shown in the last few years is strongly referred to this organic matrix for a number of reasons: algae show better performances in terms of growth rate and photosynthesis compared to terrestrial plants, not suffering from the problems of the direct and indirect land use. They are able to metabolize water rich in nitrogen, phosphorus and heavy metal compounds, also supporting the use of brackish or saline water flows, decreasing the demand for freshwater, as well as the feeding of CO2-rich
main defects of algae fuels: the high water demand, which is also a function of the type of system used for the cultivation. In general, two types can be identified: open systems, oftentimes identified with open ponds, and photobioreactors (Vo et al., 2019). The former kind represents the most economical system for algae growth, as well as the cheaper one for both production and operation (an analysis of algae growth techniques is reported in Section 1.4). Leaving aside for now the strengths and weaknesses of these devices, it should be noted that between 11 and 13 millions liters per hectare per year are required (Chinnasamy et al., 2010): hence, it is clear how important it is to be able to reduce these freshwater volumes.
Linked to the choice of the growing system is also the discourse of the contingent areal space, which has been seen to be critical also with respect to the previous generations. Open ponds take less advantage of the space available to them, being less efficient than different solutions such as photobioreactors. Still, some studies (Chisti, 2007) express confidence in how microalgae represent the only source for the production of biofuels, biodiesel in particular, capable of satisfying the global demand for transport fuels. This is due to the fact that several species show excellent qualities of lipid accumulation, reaching up to 80% in dry mass. Nevertheless, it must be considered that the lipid productivity remains low even in such cases (Bellou et al., 2014). Chemical energy is stored in the form of oils when algae have to withstand adverse environmental conditions such as food deprivation or photo-oxidative stress; it can be used in the presence of short chain alcohols for transesterification to obtain biodiesel or catalytic deoxygenation/hydrogenation of fatty acids into linear hydrocarbons (Riazi and Chiaramonti, 2017). Overall, oil is produced by microalgae more efficiently than crop plantsOverall, oil is produced by microalgae more efficiently than crop plants, with yield per unit area way better than even the best oilseed crops (Rodolfi et al. 2009). Productions of bioethanol, biohydrogen and long-chain hydrocarbons from microalgae are possible as well, and are actually subject of investigations. Moreover, another pursuable route consists in converting algal biomass to biogas by the means of anaerobic fermentation (Wijffels and Barbosa, 2010). By the means of fermentation, one can recover the residual algal biomass resulting from oil extraction to obtain methane or ethanol, or alternatively exploit it as fertilizer or feed (Rodolfi et al. 2009). Other than water demand, the other main obstacle that prevents the declaration of the third generation as the biofuel of the future is the need of large amounts of nutrients, N and P in particular. This entails a two-fold problem: fertilizer production may end up releasing more GHGs emissions than those avoided by employing algae based biofuels, hindering the commercial viability as well due to costs higher than fuels derived from different sources, other than the high energy demand required for CO2
1.4 Microalgae: a multipurpose environmental tool 21
open raceway ponds, in order to achieve a robust industrial scale production, downstream processing is reported to account for about 60% of the overall biodiesel production cost (Kim et al. 2013). Again, the need of integrating different processes in closed-loop cycles manifests itself.
Other shortcomings are related to the challenge of assuring the presence of appropri-ate conditions for the growth of the selected species, which should be identified between strains with lipid productivity as high as possible, and the lack of data regarding large-scale microalgae cultures (Rodolfi et al. 2009).
1.3.4
The fourth generation
In order to contain the costs related to algae-based biofuels, it is possible to intervene accord-ing to two philosophies: by evolvaccord-ing the technology behind the engineeraccord-ing of production processes, ideally optimizing both operating conditions and cost of the devices, or by improv-ing biological efficiency, increasimprov-ing the growth rate and lipid content inasmuch as possible (Davis et al., 2011). Pursuing this latter would lead to fourth generation biofuels. With this notion biofuels developed through the use of novel synthetic biology tools are identified. The predominant group is made up of biofuels synthesized from algae altered by the means of metabolic engineering and genome editing methods. Genome editing refers to an engi-neering technique capable of modifying the genomic DNA in a site-specific manner. To this class belongs genome editing systems based on Zinc-Finger Nuclease (ZFN), Transcription Activator-Like Effector Nucleases (TALEN) as well as the system acclaimed as revolutionary, the Clustered Regularly Interspaced Palindromic Sequences (CRISPR)/CRISPR-associated protein 9 (Cas9) (Maeda et al., 2018).
Employing tailor-suited biomass can markedly diminish processing costs associated with the harvest when compared with traditional approach. On the whole, notable production yields of genetically-modified algae with high lipid content, potentially better adaptivity and increased carbon capture capabilities are the main advantages of the fourth generation of biofuels. In contrast, the initial investment is very high, and research is still at its infant stage. To delve deeper into this interesting topic, see the review article by Aro (Aro, 2016).
1.4
Microalgae: a multipurpose environmental tool
Generally, the term algae refers to an artificial, non-cohesive and polyphyletic assembly of photosynthetic organisms, capable of tolerating a wide range of physiochemical conditions (temperature, pH values, light intensity, nutrient availability and salinity). This collection
